Diagnosing Subsurface Vertical Velocities from High-Resolution Sea Surface Fields

Lei Liu State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China

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Huijie Xue State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China
School of Marine Sciences, University of Maine, Orono, Maine

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Hideharu Sasaki Application Laboratory, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan

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Abstract

Using the extended “interior + surface quasigeostrophic” method from the 2019 study by Liu et al. (hereafter L19), subsurface density and horizontal velocities can be reconstructed from sea surface buoyancy and surface height. This study explores the potential of L19 for diagnosing the upper-ocean vertical velocity w field from high-resolution surface information, employing the 1/30° horizontal resolution OFES model output. Specifically, we employ the L19-reconstructed density and horizontal velocity fields in a diabatic version of the omega equation that incorporates a simplified parameterization for turbulent vertical mixing. The w diagnosis is evaluated against OFES output in the Kuroshio Extension region of the North Pacific, and the result indicates that the L19 method constitutes an effective framework. Statistically, the OFES-simulated and L19-diagnosed w fields have a 2-yr-averaged spatial correlation of 0.42–0.51 within the mixed layer and 0.51–0.67 throughout the 1000-m upper ocean below the mixed layer. Including the diabatic turbulent mixing effect has improved the w diagnoses inside the mixed layer, particularly for the cold-season days with the largest correlation improvement reaching 0.31. Our encouraging results suggest that the L19 method can be applied to the high-resolution sea surface height data from the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission for reconstructing 3D hydrodynamic conditions of the upper ocean.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Huijie Xue, huijiexue@scsio.ac.cn

Abstract

Using the extended “interior + surface quasigeostrophic” method from the 2019 study by Liu et al. (hereafter L19), subsurface density and horizontal velocities can be reconstructed from sea surface buoyancy and surface height. This study explores the potential of L19 for diagnosing the upper-ocean vertical velocity w field from high-resolution surface information, employing the 1/30° horizontal resolution OFES model output. Specifically, we employ the L19-reconstructed density and horizontal velocity fields in a diabatic version of the omega equation that incorporates a simplified parameterization for turbulent vertical mixing. The w diagnosis is evaluated against OFES output in the Kuroshio Extension region of the North Pacific, and the result indicates that the L19 method constitutes an effective framework. Statistically, the OFES-simulated and L19-diagnosed w fields have a 2-yr-averaged spatial correlation of 0.42–0.51 within the mixed layer and 0.51–0.67 throughout the 1000-m upper ocean below the mixed layer. Including the diabatic turbulent mixing effect has improved the w diagnoses inside the mixed layer, particularly for the cold-season days with the largest correlation improvement reaching 0.31. Our encouraging results suggest that the L19 method can be applied to the high-resolution sea surface height data from the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission for reconstructing 3D hydrodynamic conditions of the upper ocean.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Huijie Xue, huijiexue@scsio.ac.cn
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